The plots of Rt over time are showing downward trends, following a period of increased transmission from the middle of the November lockdown to around the introduction of the national Tier 4 restrictions and the beginning of the Christmas period. These result in many of the Rt values being below 1, with the exception of the SW, NE, EM and NW where the number of infections is increasing (SW, NE) or plateauing (EM, NW).
Incidence of deaths which had levelled off during the last week of November / first week of December, with some falls noted in the North East, North West, and Yorkshire & Humberside, started to climb significantly throughout December and early January in all regions. The deaths that we are currently observing will be predominantly from infections acquired pre-Christmas. The deaths, which are now at a level similar to the first wave (e.g. SE and EE) are predicted to start falling soon, once the majority of the pre-Christmas infections have been resolved.
It is now possible to estimate that the Tier 4 restriction introduced on Saturday 19th December, in combination with the school holidays and reduced movements around the Christmas period, have contributed to a downward trends in Rt and the slowing down in the growth in the number of infections in most regions. The impact of the lockdown announced on 5th January cannot yet be measured, and therefore any potential effects are excluded from the discussion of these results. Regardless, the prevalence of infection remains high and the demand on healthcare services is currently extreme, so continued restrictions are needed to lower these levels and to maintain control over transmission.
Real-time tracking of an epidemic, as data accumulate over time, is an essential component of a public health response to a new outbreak. A team of statistical modellers at the MRC Biostatistics Unit (BSU), University of Cambridge, are working to provide regular now-casts and forecasts of COVID-19 infections and deaths. This information feeds directly to the SAGE sub-group, Scientific Pandemic Influenza sub-group on Modelling (SPI-M), and to regional Public Health England (PHE) teams.
We fit a transmission model (Birrell et al. 2020) to a number of data sources (see ‘Data Sources’), to reconstruct the number of new COVID-19 infections over time in different age groups and NHS regions, estimate a measure of ongoing transmission and predict the number of new COVID-19 deaths.
We use:
Data are stratified into eight age groups: <1, 1-4, 5-14, 15-24, 25-44, 45-64, 65-74, 75+, and the NHS England regions (North East and Yorkshire, North West, Midlands, East of England, London, South East, South West).
Value of \(R_t\), the average number of secondary infections due to a typical infection today.
## `summarise()` ungrouping output (override with `.groups` argument)The percentage of a given group that has been infected.
## `summarise()` ungrouping output (override with `.groups` argument)NB: negative growth rates are rates of decline. Values are daily changes.
| Region | Median | 95% CrI (lower) | 95% CrI (upper) |
|---|---|---|---|
| England | -0.02 | -0.04 | 0.00 |
| East of England | -0.06 | -0.10 | -0.02 |
| East Midlands | -0.01 | -0.06 | 0.02 |
| London | -0.09 | -0.12 | -0.05 |
| North East | 0.00 | -0.04 | 0.05 |
| North West | -0.01 | -0.05 | 0.02 |
| South East | -0.08 | -0.12 | -0.04 |
| South West | 0.01 | -0.04 | 0.06 |
| West Midlands | -0.07 | -0.11 | -0.02 |
| Yorkshire and The Humber | -0.04 | -0.08 | 0.00 |
Halving times in days, if a region shows growth than value will be NA.
| Region | Median | 95% CrI (lower) | 95% CrI (upper) |
|---|---|---|---|
| England | 28.65 | 16.09 | 221.96 |
| East of England | 10.52 | 6.27 | 30.82 |
| East Midlands | 48.83 | 12.21 | NA |
| London | 7.73 | 5.27 | 14.05 |
| North East | NA | 17.20 | NA |
| North West | 62.78 | 13.91 | NA |
| South East | 8.35 | 5.38 | 17.33 |
| South West | NA | 17.43 | NA |
| West Midlands | 9.75 | 5.79 | 29.10 |
| Yorkshire and The Humber | 17.75 | 8.12 | NA |
Doubling times in days, if a region shows decline then the value will be NA.
| Region | Median | 95% CrI (lower) | 95% CrI (upper) |
|---|---|---|---|
| England | NA | NA | NA |
| East of England | NA | NA | NA |
| East Midlands | NA | 28.76 | NA |
| London | NA | NA | NA |
| North East | 144.20 | 15.26 | NA |
| North West | NA | 29.41 | NA |
| South East | NA | NA | NA |
| South West | 80.87 | 12.24 | NA |
| West Midlands | NA | NA | NA |
| Yorkshire and The Humber | NA | 193.49 | NA |
NB: negative growth rates are rates of decline. Values are daily changes.
| Region | Median | 95% CrI (lower) | 95% CrI (upper) |
|---|---|---|---|
| England | 0.00 | -0.01 | 0.01 |
| East of England | -0.02 | -0.03 | 0.00 |
| East Midlands | 0.01 | -0.01 | 0.04 |
| London | -0.03 | -0.04 | -0.01 |
| North East | 0.03 | 0.00 | 0.06 |
| North West | 0.02 | 0.00 | 0.04 |
| South East | -0.02 | -0.04 | -0.01 |
| South West | 0.03 | 0.00 | 0.06 |
| West Midlands | -0.02 | -0.03 | 0.00 |
| Yorkshire and The Humber | -0.01 | -0.02 | 0.02 |
Halving times in days, if a region shows growth than value will be NA.
| Region | Median | 95% CrI (lower) | 95% CrI (upper) |
|---|---|---|---|
| England | 313.85 | 75.47 | NA |
| East of England | 44.48 | 23.40 | NA |
| East Midlands | NA | 90.52 | NA |
| London | 25.34 | 18.28 | 50.94 |
| North East | NA | NA | NA |
| North West | NA | NA | NA |
| South East | 28.69 | 19.06 | 84.31 |
| South West | NA | 1451.03 | NA |
| West Midlands | 33.87 | 19.89 | NA |
| Yorkshire and The Humber | 136.65 | 30.73 | NA |
Doubling times in days, if a region shows decline then the value will be NA.
| Region | Median | 95% CrI (lower) | 95% CrI (upper) |
|---|---|---|---|
| England | NA | 121.93 | NA |
| East of England | NA | 190.12 | NA |
| East Midlands | 55.23 | 18.54 | NA |
| London | NA | NA | NA |
| North East | 26.77 | 12.32 | 1331.95 |
| North West | 35.13 | 16.23 | 2966.61 |
| South East | NA | NA | NA |
| South West | 26.15 | 11.34 | NA |
| West Midlands | NA | 1562.76 | NA |
| Yorkshire and The Humber | NA | 39.56 | NA |
The blue lines is show when interventions have been introduced (lockdown on 23 Mar and the relaxation of measures on 11 May), and the red line shows the date these results were produced (11 Jan).
## Warning: `arrange_()` is deprecated as of dplyr 0.7.0.
## Please use `arrange()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.The figure below shows the probability that \(R_t\) is greater than 1 (ie: the number of infections is growing) in each region over time. Clicking the regions in the legend allows lines to be added or removed from the figure.
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colorsCopyright © MRC Biostatistics Unit, University of Cambridge